在 Python 中使用 multiprocessing.shared_memory.ShareMemory 时出现分段错误(退出代码 139(被信号 11 中断:SIGSEGV))

segmentation fault (exit code 139 (interrupted by signal 11: SIGSEGV)) when using multiprocessing.shared_memory.ShareMemory in Python

我正在尝试将 List[np.ndarray] 加载到 shared_memory 中,以便其他进程可以直接访问此 shared_memory 并恢复原始 List[np.ndarray] 而无需复制 List[np.ndarray] 进入每一个过程。详细的动机和我之前的问题有关:share read-only generic complex python object with int, list of numpy array, tuple, etc. as instance field between multiprocessing

我写了下面的代码(python版本:3.8.12,Numpy:1.20.3,MacOS):

encode_nd_arr_list():给定List[np.ndarray],我可以得到List of share_memory namedecode_nd_arr_list():给定List of share_memory name,我可以恢复原来的List[np.ndarray]

from typing import List, Tuple
import numpy as np
from multiprocessing.shared_memory import SharedMemory
from multiprocessing.managers import SharedMemoryManager


def encode_nd_arr_list(
        smm: SharedMemoryManager,
        nd_arr_list: List[np.ndarray]
):

    shm_name_list = []
    shape, dtype = nd_arr_list[0].shape, nd_arr_list[0].dtype
    print(shape)
    print(dtype)
    for nd_arr in nd_arr_list:
        shm = smm.SharedMemory(size=nd_arr.nbytes)
        shm_arr = np.ndarray(shape=shape, dtype=dtype, buffer=shm.buf)
        np.copyto(shm_arr, nd_arr)
        shm_name_list.append(shm.name)
    return shm_name_list, shape, dtype


def decode_nd_arr_list(
        shm_name_list: List[str],
        shape: Tuple[int],
        dtype: np.dtype
):

    nd_array_list = []
    for shm_name in shm_name_list:
        print("----------")
        shm = SharedMemory(shm_name)
        nd_arr = np.ndarray(shape=shape, dtype=dtype, buffer=shm.buf)
        print("nd_arr:", nd_arr)
        nd_array_list.append(nd_arr)
        print("nd_array_list:", nd_array_list)
    return nd_array_list


if __name__ == '__main__':
    arr = np.array([[1, 2, 3], [2, 3, 4], [3, 4, 5]])
    nd_arr_list = [arr, arr + 1, arr + 2]
    print(nd_arr_list)
    with SharedMemoryManager() as smm:
        shm_name_list, shape, dtype = encode_nd_arr_list(smm, nd_arr_list)
        print(shm_name_list)
        print(shape)
        print(dtype)
        res = decode_nd_arr_list(shm_name_list, shape, dtype)
        print("------------")
        print(res)

然而,当我运行它在PyCharm时,控制台显示Process finished with exit code 139 (interrupted by signal 11: SIGSEGV)。当我在终端中运行时,它显示segmentation fault,没有任何错误信息。

我的问题:

  1. 我的这个错误是什么意思?

  2. 我怎样才能使我的代码工作?谢谢。

decode_nd_arr_list 方法中循环的每次迭代中使用的缓冲区在相应的 SharedMemory 对象超出范围并导致段错误后关闭。您实质上是在尝试访问不再有效的内存。

为了修复它,您可以创建一个自定义对象来环绕 ndarray 并存储 SharedMemory 以防止它超出范围。

示例:

from typing import List, Tuple
import numpy as np
from multiprocessing.shared_memory import SharedMemory
from multiprocessing.managers import SharedMemoryManager


class SHMArray(np.ndarray):

    def __new__(cls, input_array, shm=None):
        obj = np.asarray(input_array).view(cls)
        obj.shm = shm
        return obj

    def __array_finalize__(self, obj):
        if obj is None: return
        self.shm = getattr(obj, 'shm', None)

def encode_nd_arr_list(
        smm: SharedMemoryManager,
        nd_arr_list: List[np.ndarray]
):

    shm_name_list = []
    shape, dtype = nd_arr_list[0].shape, nd_arr_list[0].dtype
    print(shape)
    print(dtype)
    for nd_arr in nd_arr_list:
        shm = smm.SharedMemory(size=nd_arr.nbytes)
        shm_arr = np.ndarray(shape=shape, dtype=dtype, buffer=shm.buf)
        np.copyto(shm_arr, nd_arr)
        shm_name_list.append(shm.name)
    return shm_name_list, shape, dtype


def decode_nd_arr_list(
        shm_name_list: List[str],
        shape: Tuple[int],
        dtype: np.dtype
):

    nd_array_list = []
    for shm_name in shm_name_list:
        print("----------")
        shm = SharedMemory(shm_name)
        nd_arr = SHMArray(np.ndarray(shape=shape, dtype=dtype, buffer=shm.buf), shm)
        print("nd_arr:", nd_arr)
        nd_array_list.append(nd_arr)
        print("nd_array_list:", nd_array_list)
    return nd_array_list


if __name__ == '__main__':
    arr = np.array([[1, 2, 3], [2, 3, 4], [3, 4, 5]])
    nd_arr_list = [arr, arr + 1, arr + 2]
    print(nd_arr_list)
    with SharedMemoryManager() as smm:
        shm_name_list, shape, dtype = encode_nd_arr_list(smm, nd_arr_list)
        print(shm_name_list)
        print(shape)
        print(dtype)
        res = decode_nd_arr_list(shm_name_list, shape, dtype)
        print("------------")
        print(res)

参考:https://github.com/numpy/numpy/issues/18294#issuecomment-771329575